




'''simple docstring'''

import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
						from .tokenization_rembert import RemBertTokenizer
else:
						a       :						List[Any]								=		None

a       :						List[str]								=		logging.get_logger(__name__)
a       :						Optional[int]								=		{'''vocab_file''': '''sentencepiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

a       :						int								=		{
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
    '''tokenizer_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/tokenizer.json''',
    },
}

a       :						List[str]								=		{
    '''google/rembert''': 256,
}

a       :						Tuple								=		'''▁'''



class 		SCREAMING_SNAKE_CASE__  (			_UpperCamelCase	):
			__SCREAMING_SNAKE_CASE    =			VOCAB_FILES_NAMES
			__SCREAMING_SNAKE_CASE    =			PRETRAINED_VOCAB_FILES_MAP
			__SCREAMING_SNAKE_CASE    =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__SCREAMING_SNAKE_CASE    =			RemBertTokenizer





			def __init__(      self						:    Optional[int]      ,		a_						:    Optional[Any]=None      ,		a_						:    Optional[int]=None      ,		a_						:    List[Any]=True      ,		a_						:    List[str]=True      ,		a_						:    str=False      ,		a_						:    Optional[Any]="[CLS]"      ,		a_						:    Optional[Any]="[SEP]"      ,		a_						:    List[Any]="<unk>"      ,		a_						:    Any="[SEP]"      ,		a_						:    List[Any]="<pad>"      ,		a_						:    List[str]="[CLS]"      ,		a_						:    Optional[Any]="[MASK]"      ,		**a_						:    str      ,		):



						"""simple docstring"""




						__snake_case			=		AddedToken(a_      ,		lstrip=a_      ,		rstrip=a_							) if isinstance(a_      ,		a_							) else mask_token

						super().__init__(
						    a_      ,		tokenizer_file=a_      ,		do_lower_case=a_      ,		remove_space=a_      ,		keep_accents=a_      ,		bos_token=a_      ,		eos_token=a_      ,		unk_token=a_      ,		sep_token=a_      ,		pad_token=a_      ,		cls_token=a_      ,		mask_token=a_      ,		**a_      ,		)

						__snake_case			=		do_lower_case
						__snake_case			=		remove_space
						__snake_case			=		keep_accents
						__snake_case			=		vocab_file
						__snake_case			=		False if not self.vocab_file else True





			def 							A (      self						:    Optional[Any]      ,		a_						:    List[int]      ,		a_						:    Optional[List[int]] = None							):



						"""simple docstring"""




						__snake_case			=		[self.sep_token_id]
						__snake_case			=		[self.cls_token_id]
						if token_ids_a is None:
									return cls + token_ids_a + sep
						return cls + token_ids_a + sep + token_ids_a + sep





			def 							A (      self						:    Union[str, Any]      ,		a_						:    List[int]      ,		a_						:    Optional[List[int]] = None      ,		a_						:    bool = False							):



						"""simple docstring"""




						if already_has_special_tokens:
									if token_ids_a is not None:
												raise ValueError(
												    "You should not supply a second sequence if the provided sequence of "
												    "ids is already formatted with special tokens for the model."							)
									return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

						if token_ids_a is not None:
									return [1] + ([0] * len(a_							)) + [1] + ([0] * len(a_							)) + [1]
						return [1] + ([0] * len(a_							)) + [1]





			def 							A (      self						:    Dict      ,		a_						:    List[int]      ,		a_						:    Optional[List[int]] = None							):



						"""simple docstring"""




						__snake_case			=		[self.sep_token_id]
						__snake_case			=		[self.cls_token_id]

						if token_ids_a is None:
									return len(cls + token_ids_a + sep							) * [0]
						return len(cls + token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1]






			def 							A (      self						:    int      ,		a_						:    str      ,		a_						:    Optional[str] = None							):



						"""simple docstring"""




						if not os.path.isdir(a_							):
									logger.error("Vocabulary path ({}) should be a directory".format(a_							)							)
									return
						__snake_case			=		os.path.join(
						    a_      ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

						if os.path.abspath(self.vocab_file							) != os.path.abspath(a_							):
									copyfile(self.vocab_file      ,		a_							)

						return (out_vocab_file,)











'''simple docstring'''







def 						_A      ( UpperCAmelCase = 1      ,UpperCAmelCase = 1000						):






   '''simple docstring'''







   A__       =     1
   A__       =     0

   for divide_by_number in range(UpperCAmelCase      ,digit + 1						):
      A__       =     []
      A__       =     numerator
      for _ in range(1      ,digit + 1						):
         if now_divide in has_been_divided:
            if longest_list_length < len(UpperCAmelCase						):
               A__       =     len(UpperCAmelCase						)
               A__       =     divide_by_number
         else:
            has_been_divided.append(UpperCAmelCase						)
            A__       =     now_divide * 10 % divide_by_number

   return the_digit


# Tests
if __name__ == "__main__":
    import doctest

    doctest.testmod()


